Identification of aberrant luminal progenitors and mTORC1 as a potential breast cancer prevention target in BRCA2 mutation carriers

Midkine links aging with breast cancer-A new predictor of cancer risk

Despite aging being one of the strongest risk factors for cancer, little is known about the biological mechanisms that promote tumor initiation. In this issue of Cancer Cell, Yan et al. address this fundamental question in the context of breast cancer and report that midkine is upregulated during the aging process and can promote tumorigenesis.

Tumor initiation and early tumorigenesis: molecular mechanisms and interventional targets

Tumorigenesis is a multistep process, with oncogenic mutations in a normal cell conferring clonal advantage as the initial event. However, despite pervasive somatic mutations and clonal expansion in normal tissues, their transformation into cancer remains a rare event, indicating the presence of additional driver events for progression to an irreversible, highly heterogeneous, and invasive lesion. Recently, researchers are emphasizing the mechanisms of environmental tumor risk factors and epigenetic alterations that are profoundly influencing early clonal expansion and malignant evolution, independently of inducing mutations. Additionally, clonal evolution in tumorigenesis reflects a multifaceted interplay between cell-intrinsic identities and various cell-extrinsic factors that exert selective pressures to either restrain uncontrolled proliferation or allow specific clones to progress into tumors. However, the mechanisms by which driver events induce both intrinsic cellular competency and remodel environmental stress to facilitate malignant transformation are not fully understood. In this review, we summarize the genetic, epigenetic, and external driver events, and their effects on the co-evolution of the transformed cells and their ecosystem during tumor initiation and early malignant evolution. A deeper understanding of the earliest molecular events holds promise for translational applications, predicting individuals at high-risk of tumor and developing strategies to intercept malignant transformation.

Novel Cancer Prevention Strategies in Individuals With Hereditary Cancer Syndromes: Focus on BRCA1, BRCA2, and Lynch Syndrome

Germline pathogenic variants (PVs) in the BRCA1 and BRCA2 genes confer elevated risks of breast, ovarian, and other cancers. Lynch syndrome (LS) is associated with increased risks of multiple cancer types including colorectal and uterine cancers. Current cancer risk mitigation strategies have focused on pharmacologic risk reduction, enhanced surveillance, and preventive surgeries. While these approaches can be effective, they stand to be improved on because of either limited efficacy or undesirable impact on quality of life. The current review summarizes ongoing investigational efforts in cancer risk prevention strategies for patients with germline PVs in BRCA1, BRCA2, or LS-associated genes. These efforts span radiation, surgery, and pharmacology including vaccine strategies. Understanding the molecular events involved in the premalignant to malignant transformation in high-risk individuals may ultimately contribute significantly to novel prevention strategies.

The prognostic genes model of breast cancer drug resistance based on single-cell sequencing analysis and transcriptome analysis

Breast cancer (BC) represents a multifaceted malignancy, with escalating incidence and mortality rates annually. Chemotherapy stands as an indispensable approach for treating breast cancer, yet drug resistance poses a formidable challenge. Through transcriptome data analysis, we have identified two sets of genes exhibiting differential expression in this context. Furthermore, we have confirmed the overlap between these genes and those associated with exosomes, which were subsequently validated in cell lines. The investigation screened the identified genes to determine prognostic markers for BC and utilized them to formulate a prognostic model. The disparities in prognosis and immunity between the high- and low-risk groups were validated using the test dataset. We have discerned different BC subtypes based on the expression levels of prognostic genes in BC samples. Variations in prognosis, immunity, and drug sensitivity among distinct subtypes were examined. Leveraging data from single-cell sequencing and prognostic gene expression, the AUCell algorithm was employed to score individual cell clusters and analyze the pathways implicated in high-scoring groups. Prognostic genes (CCT4, CXCL13, MTDH, PSMD2, and RAB27A) were subsewoquently validated using RT-qPCR. Consequently, we have established a model for predicting prognosis in breast cancer that hinges on drug resistance and ERGs. Furthermore, we have evaluated the prognostic value of this model. The genes identified as prognostic markers can now serve as a reference for precise treatment of this condition.